Evaluating the articulation of programme theory in practice as observed in Quality Improvement initiatives

Background: The Action-Effect Method(AEM) was co-developed by NIHR CLAHRC Northwest London (CLAHRC NWL) researchers and QI practitioners, building on Driver Diagrams(DD). This study aimed to determine AEM effectiveness in terms of technical aspects (how diagrams produced in practice compared with theoretical ideals) and social aspects (how engagement with the method related to social benefits). Methods Diagrams were scored on criteria developed on theoretical ideals of programme theory. 65 programme theory diagrams were reviewed (21 published Driver Diagrams (External DDs), 22 CLAHRC NWL Driver Diagrams (Internal DDs), and 21 CLAHRC NWL Action-Effect Diagrams(AEDs)). Social functions were studied through ethnographic observation of frontline QI teams in AEM sessions facilitated by QI experts. Qualitative analysis used inductive and deductive coding. Results ANOVA indicated the AEM significantly improved the quality of programme theory diagrams over Internal and External DDs on an average of 5 criteria from an 8-point assessment. Articulated aims were more likely to be patient-focused and high-level in AEDs than DDs. The cause/effect relationships from intervention to overall aim also tended to be clearer and were more likely than DDs to contain appropriate measure concepts. Using the AEM also served several social functions such as facilitating dialogue among multidisciplinary teams, and encouraging teams to act scientifically and pragmatically about planning and measuring QI interventions. Implications: The Action-Effect Method developed by CLAHRC NWL resulted in improvements over Driver Diagrams in articulating programme theory, which has wide-ranging benefits to quality improvement, including encouraging broad multi-disciplinary buy-in to clear aims and pre-planning a rigorous evaluation strategy

Minimum d-dimensional arrangement with fixed points

In the Minimum $d$-Dimensional Arrangement Problem (d-dimAP) we are given a graph with edge weights, and the goal is to find a 1-1 map of the vertices into $\mathbb{Z}^d$ (for some fixed dimension $d\geq 1$) minimizing the total weighted stretch of the edges. This problem arises in VLSI placement and chip design. Motivated by these applications, we consider a generalization of d-dimAP, where the positions of some of the vertices (pins) is fixed and specified as part of the input. We are asked to extend this partial map to a map of all the vertices, again minimizing the weighted stretch of edges. This generalization, which we refer to as d-dimAP+, arises naturally in these application domains (since it can capture blocked-off parts of the board, or the requirement of power-carrying pins to be in certain locations, etc.). Perhaps surprisingly, very little is known about this problem from an approximation viewpoint. For dimension $d=2$, we obtain an $O(k^{1/2} \cdot \log n)$-approximation algorithm, based on a strengthening of the spreading-metric LP for 2-dimAP. The integrality gap for this LP is shown to be $\Omega(k^{1/4})$. We also show that it is NP-hard to approximate 2-dimAP+ within a factor better than \Omega(k^{1/4-\eps}). We also consider a (conceptually harder, but practically even more interesting) variant of 2-dimAP+, where the target space is the grid $\mathbb{Z}_{\sqrt{n}} \times \mathbb{Z}_{\sqrt{n}}$, instead of the entire integer lattice $\mathbb{Z}^2$. For this problem, we obtain a $O(k \cdot \log^2{n})$-approximation using the same LP relaxation. We complement this upper bound by showing an integrality gap of $\Omega(k^{1/2})$, and an \Omega(k^{1/2-\eps})-inapproximability result. Our results naturally extend to the case of arbitrary fixed target dimension $d\geq 1$

The Relationship between Quality Improvement and Health Information Technology Use in Local Health Departments

This research examined if there is a relationship between engagement in quality improvement (QI) and health information technology (HIT) for local health departments (LHDs) controlling for workforce, finance, population, and governance structure. This was a cross-sectional study that analyzed data obtained from the Core questions and Module 1 in the NACCHO 2010 Profile of LHDs. Descriptive statistics, bivariate analyses, and logistic regression analyses were conducted. Findings suggest that LHD engagement in QI has a relationship with utilization of HIT including electronic health records, practice management systems, and electronic syndromic surveillance systems. This study provides baseline information about the HIT use of LHDs. LHDs and their system partners (hospitals, federally qualified health centers, and primary care providers) that utilize HIT as part of their QI decision making may have an easier time of using data to support evidence-based decision making and implementing the provisions of the Patient Protection and Affordable Care Act of 2010 in order to achieve population health for all